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This is a continuation of the previous post on using Google Analytics .
Now that we have downloaded and plotted the data- we try and fit time series to the website data to forecast future traffic.
1) Google Analytics has 0 predictive analytics, it is just descriptive analytics and data visualization models (including the recent social analytics). However you can very well add in basic TS function using R to the GA API.
Why do people look at Website Analytics? To know today’s traffic and derive insights for the Future
2) Web Data clearly follows a 7 day peak and trough for weekly effects (weekdays and weekends), this is also true for hourly data …and this can be used for smoothing historic web data for future forecast.
3) On an advanced level, any hugely popular viral posts can be called a level shift (not drift) and accoringly dampened.
Test and Control!
Similarly using ARIMAX, we can factor in quantity and tag of posts as X regressor variables.
and now the code-( dont laugh at the simplicity please, I am just tinkering and playing with data here!)
You need to copy and paste the code at the bottom of this post
if you want to download your GA data down first.
Note I am using lubridate ,forecast and timeSeries packages in this section.
#Plotting the Traffic plot(ga.data$data[,2],type="l")
#Using package lubridate to convert character dates into time library(lubridate) ga.data$data[,1]=ymd(ga.data$data[,1]) ls() dataset1=ga.data$data names(dataset1) <- make.names(names(dataset1)) str(dataset1) head(dataset1) dataset2 <- ts(dataset1$ga.visitors,start=0,frequency = frequency(dataset1$ga.visitors), names=dataset1$ga.date) str(dataset2) head(dataset2) ts.test=dataset2[1:200] ts.control=dataset2[201:275] #Note I am splitting the data into test and control here fitets=ets(ts.test) plot(fitets) testets=ets(ts.control,model=fitets) accuracy(testets) plot(testets) spectrum(ts.test,method='ar') decompose(ts.test) library("TTR") bb=SMA(dataset2,n=7)#We are doing a simple moving average for every 7 days. Note this can be 24 hrs for hourly data, or 30 days for daily data for month # to month comparison or 12 months for annual #We notice that Web Analytics needs sommethening for every 7 thday as there is some relation to traffic on weekedays /weekends /same time last week head(dataset2,40) head(bb,40) par(mfrow=c(2,1)) plot(bb,type="l",main="Using Seven Day Moving Average for Web Visitors") plot(dataset2,main="Original Data")
Though I still wonder why the R query, gA R code /package could not be on the cloud (why it needs to be downloaded)– cloud computing Gs?
Also how about adding some MORE predictive analytics to Google Analytics, chaps!
To be continued-
auto.arima() and forecasts!!!
and adapting the idiosyncratic periods and cycles of web analytics to time series !!
Over the Christmas break, I created a Google Adwords campaign using the $100 credit generously given by Google. I did it using my alumni id, even though I have a perfectly normal gmail id. I guess if Google allows me to use the credit on any account- well I will take it. and so a free experiment was borne.
But whom to target -with Google- but Google itself. It seemed logical
So I created a campaign for the names of prominent Googlers (from a list of Google + at
) and limited the ad location to Mountain View, California.
NULL HYPOTHESIS- People who are googled a lot from within the office are either popular or just checking themselves.
My ad was-
Hire Ajay Ohri
or see screenshot below.
Here are the results-88 clicks and 43000 impressions (and 83$ of Google’s own money)
clearly Vic Gundotra is googled a lot within Mountain View, California. Does He Google himself.
so is Matt Cutts. Does HE Google himself or does he get elves to help him.
to my disappointment not many people clicked my LI offer, I am still blogging
and there were few clicks on Marissa Myers. Why Google her when she is right down the corridor.
The null hypothesis is thus rejected. Also most clicks were from display and not from search.
I need to do something better to do with Christmas break this year. I still got a credit of 16$ left.
Imagine a world in which your car tracks everywhere you go. Over a period of time, it builds up a database of your driving habits, how long you stay at particular kinds of dining places, entertainment places (ahem!) , and the days, and times you do it. You can no longer go to massage parlours without your data being checked by your car software admin (read – your home admin)
And that data is mined using machine learning algols to give you better ads for pizzas, or a reminder for food after every 3 hours , or an ad for beer every Thursday after 8 pm .
Welcome Brave New World!
So I tried to move without a search engine , and only social sharing, but for a small blog like mine, that means almost 75% of traffic comes via search engines.
Maybe the ratio of traffic from search to social will change in the future,
I have now enough data to conclude search is the ONLY statistically significant driver of traffic ( for a small blog)
If you are a blogger you should definitely try and give the tools at Google Webmaster a go,
URL Googlebot type Fetch Status Fetch date
http://decisionstats.com/ Web Denied by robots.txt 1/19/12 8:25 PM
http://decisionstats.com/ Web Success URL and linked pages submitted to index 12/27/11 9:55 PM
Also from Google Analytics, I see that denying search traffic doesnot increase direct/ referral traffic in any meaningful way.
So my hypothesis that some direct traffic was mis-counted as search traffic due to Chrome, toolbar search – well the hypothesis was wrong
Also Google seems to drop url quite quickly (within 18 hours) and I will test the rebound in SERPs in a few hours. I was using meta tags, blocked using robots.txt, and removal via webmasters ( a combination of the three may have helped)
To my surprise search traffic declined to 5-10, but it did not become 0. I wonder why that happens (I even got a few Google queries per day) and I was blocking the “/” fron robots.txt.
Net Net- The numbers below show- as of now , in a non SOPA, non Social world, Search Engines remain the webmasters only true friend (till they come up with another panda or whatever update )
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